CoCo: Sound and adaptive replacement of java collections

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Abstract

Inefficient use of Java containers is an important source of run-time inefficiencies in large applications. This paper presents an application-level dynamic optimization technique called CoCo, that exploits algorithmic advantages of Java collections to improve performance. CoCo dynamically identifies optimal Java collection objects and safely performs run-time collection replacement, both using pure Java code. At the heart of this technique is a framework that abstracts container elements to achieve efficiency and that concretizes abstractions to achieve soundness. We have implemented part of the Java collection framework as instances of this framework, and developed a static CoCo compiler to generate Java code that performs optimizations. This work is the first step towards achieving the ultimate goal of automatically optimizing away semantic inefficiencies. © 2013 Springer-Verlag Berlin Heidelberg.

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Xu, G. (2013). CoCo: Sound and adaptive replacement of java collections. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7920 LNCS, pp. 1–26). Springer Verlag. https://doi.org/10.1007/978-3-642-39038-8_1

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